課程信息
4.9
12 個評分
4 個審閱
專項課程

第 4 門課程(共 4 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
高級

高級

完成時間(小時)

完成時間大約為13 小時

建議:4 hours/week...
可選語言

英語(English)

字幕:英語(English), 法語(French)
專項課程

第 4 門課程(共 4 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
高級

高級

完成時間(小時)

完成時間大約為13 小時

建議:4 hours/week...
可選語言

英語(English)

字幕:英語(English), 法語(French)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 3 小時

Week 1 - Identify DataSet and UseCase

In this module, the basic process model used for this capstone project is introduced. Furthermore, the learner is required to identify a practical use case and data set...
Reading
1 個視頻 (總計 2 分鐘), 6 個閱讀材料, 2 個測驗
Video1 個視頻
Reading6 個閱讀材料
A warm welcome10分鐘
Overview of Architectural Methodologies for DataScience10分鐘
Lightweight IBM Cloud Garage Method for Data Science10分鐘
Data Sources and Use Cases10分鐘
Initial Data Exploration10分鐘
Architectural Decisions Document (ADD)10分鐘
Quiz1 個練習
Milestones Checklist Week 1
2
完成時間(小時)
完成時間為 3 小時

Week 2 - ETL and Feature Creation

This module emphasizes on the importance of ETL, data cleansing and feature creation as a preliminary step in ever data science project ...
Reading
3 個閱讀材料, 2 個測驗
Reading3 個閱讀材料
Extract Transform Load (ETL)10分鐘
Data Cleansing10分鐘
Feature Engineering10分鐘
Quiz1 個練習
Milestones Checklist Week 2
3
完成時間(小時)
完成時間為 2 小時

Week 3 - Model Definition and Training

This module emphasizes on model selection based on use case and data set. It is important to understand how those two factors impact choice of a useful model algorithm. ...
Reading
2 個閱讀材料, 2 個測驗
Reading2 個閱讀材料
Model Definition10分鐘
Model Training10分鐘
Quiz1 個練習
Milestones Checklist Week 3
4
完成時間(小時)
完成時間為 5 小時

Model Evaluation, Tuning, Deployment and Documentation

One a model is trained it is important to assess its performance using an appropriate metric. In addition, once the model is finished, it has to be made consumable by business stakeholders in an appropriate way ...
Reading
5 個閱讀材料, 3 個測驗
Reading5 個閱讀材料
Model Evaluation10分鐘
Model Deployment10分鐘
Data Product (optional)10分鐘
Create ADD - Architectural Decisions Document10分鐘
Create a Video of your final presentation10分鐘
Quiz1 個練習
Milestones Checklist Week 4

講師

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Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT

關於 IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

關於 Advanced Data Science with IBM 專項課程

As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....
Advanced Data Science with IBM

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